A merged wave field is produced by multiple energy sources, such as acoustic sources, that independently generate source signals that combine to form the merged wave field. A merged wave field can be detected using conventional sensors or transducers and can be processed using conventional signal processing techniques. Prior art signal processing systems, however, have a limited ability to selectively determine the source signals attributed to each of the independent energy sources from a detected merged wave field. Factoring a merged wave field into independent source signals is particularly difficult where the signals generated by the energy sources have a complex waveform, such as speech or other complex acoustic signals.
One type of merged wave field that is commonly detected and processed is an acoustic wave field produced by multiple acoustic sources such as by a hearing aid. Transducers, microphones or other sensors are used to detect the acoustic wave field and conventional signal processing techniques are used to process the detected acoustic signal. The acoustic wave field, however, often includes many undesirable acoustic signals or noises that mask or corrupt the desired signals to be measured, transmitted or further processed. Conventional signal processing systems have attempted to filter these undesirable acoustic signals or noises and focus on one or more of the independent acoustic signals generated by respective acoustic sources.
One of the most common complaints of hearing aid users, for example, is that background noise impedes the understanding of speech. Methods currently used to reduce background noise in hearing aids employ filtering techniques in which the frequency regions containing high noise levels are eliminated. Although some steady state noises, such as automobile or other machine sounds, can be effectively suppressed, human speech is the most difficult type of noise to filter and often the most common type of acoustic noise encountered by a hearing aid. The wearer of a hearing aid often has difficulty focusing on one voice or sound source when faced with multiple voices such as is the case in, for example, party noise or a group conversation.
Another common problem is that of reverberation produced by echoes or acoustic reflections off walls, ceiling, and other surfaces in a room. The reflection of the sound acts like additional virtual independent sound sources and can interfere with both the quality and the intelligibility of the speech being detected.
Existing signal processing techniques have been unable to effectively separate a speech signal from multiple speech sources encountered. Past attempts at suppressing undesirable speech noise have employed multiple microphones and an adaptive array approach. An array of sensors or multiple microphones receive the merged acoustic wave field, and the signals from the array of sensors are combined in such a way that the resulting output maximizes the desired signal with respect to the unwanted signals. The sound or speech that the individual wants to listen to is enhanced and the noise or unwanted acoustic signals are suppressed. This approach depends upon the interaction of the different types of microphones comprising the array and the directional characteristics of the microphones. By co-processing the signals acquired by the different microphones having different directional characteristics, the noise or unwanted signals are canceled relative to the desired sound signal.
This approach has met with limited success in simple conversational settings but is unable to provide an independent source signal from a single sound source. The signal output of the adaptive array approach provides a scalar output, i.e. a weighted sum of the acoustic signals from all of the sound sources. Thus, this approach does not provide an independent acoustic signal from a single sound source alone and therefore is limited when multiple sound sources are present. The adaptive array approach is also highly dependent on microphone directivity and the accurate determination of the bearings of the sound sources. Because of the sensitivity to source bearing errors, the adaptive array approach has difficulty handling the effects of reverberation where the reverberating sound comes from so many directions.
Accordingly, a need exists for a system and method for factoring a merged wave field, such as an acoustic wave field, into independent components or source signals attributed to independent energy sources, such as one or more sound sources. A need exists for a system and method that factors the merged wave field into independent components without being significantly affected by source bearing errors and reverberation. In particular, a need exists for a hearing aid or other type of sound receiving and processing system that can selectively process and transmit a sound signal from a single sound source among multiple sound sources.